矿山电气设备在线监测与诊断系统的设计与实现  

Design and Implementation of Online Monitoring and Diagnosis System for Mining Electrical Equipment

作　　者：胡力友 HU Liyou(Wengfu Group Co.,Ltd.,Fuquan 550500,China)

机构地区：[1]瓮福集团有限责任公司,贵州福泉550500

出　　处：《电工技术》2024年第18期222-224,共3页Electric Engineering

摘　　要：设计了一个面向非金属矿山电气设备的在线监测与诊断系统。该系统实时在线监测关键电气设备的运行参数,并通过深度学习模型分析数据模式,实现潜在故障的诊断和预警。实验结果表明,该系统可有效提高电气设备异常监测和故障诊断的精度,降低突发故障风险,从而增强了非金属矿山生产的可靠性和安全性。This study designed an online monitoring and diagnostic system for electrical equipment in non-metallic mines.The system was designed to perform real-time online monitoring of operational parameters for key electrical equipment and utilize deep learning models to analyze data patterns,achieving the diagnosis and early warning of potential faults.Experimental results indicated that the system significantly improves the accuracy of anomaly monitoring and fault diagnosis for electrical equipment,reduces the risk of sudden faults,and thus enhances the reliability and safety of non-metallic mine production.

关 键 词：非金属矿山 电气设备 监测 诊断 

分 类 号：TD60[矿业工程—矿山机电]